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Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 1.0 metric=euclidean
k=79
samples=20		 Clustering
Self Organizing Maps 1.0 x=49
y=32		 Clustering
Spectral Clustering 0.998 k=34 Clustering
clusterdp 1.0 k=21
dc=9.838981428763628		 Clustering
HDBSCAN 1.0 minPts=48
k=208		 Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=10		 Clustering
c-Means 1.0 k=14
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=206 Clustering
DIANA 1.0 metric=euclidean
k=143		 Clustering
DBSCAN 1.0 eps=6.395337928696359
MinPts=208		 Clustering
Hierarchical Clustering 1.0 method=complete
k=169		 Clustering
fanny 1.0 k=117
membexp=5.0		 Clustering
k-Means 1.0 k=92
nstart=10		 Clustering
DensityCut 1.0 alpha=0.42857142857142855
K=12		 Clustering
clusterONE 0.0 s=104
d=0.8666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=14.758472143145443
maxits=5000
convits=500		 Clustering
Markov Clustering 0.0 I=1.5721721721721722 Clustering
Transitivity Clustering 1.0 T=12.926589714967228 Clustering
MCODE 0.991 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T		 Clustering